Exploring the potential of social media crowdsourcing for post-earthquake damage assessment
Bibliographic Data
| ID | 22029319 |
|---|---|
| Authors | Lingyao Li (0000-0001-5888-8311, University of Michigan), Michelle Bensi (0000-0001-6449-1812, University of Maryland, College Park, corresponding author), Gregory B Baecher (0000-0002-9571-9282, University of Maryland, College Park), Gregory Baecher |
| Year | 2023 |
| Volume | 98 |
| Pages | 104062 |
| Publication date | 2023-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2023.104062 |
| OpenAlex | W4387643636 |
| Language | EN |
| Citations received | 9 |
| References cited | 52 |
Crowdsourcing · Damages · Data science · Political science · Social media · Volunteered Geographic Information · Warning system · World Wide Web · Computer Science · Disaster Management and Resilience · Public Relations and Crisis Communication · Seismology and Earthquake Studies
Multi-crowdsourced data fusion for modeling link-level traffic resilience to adverse weather events
Fine-scale spatiotemporal earthquake casualty risk assessment considering building function types
Feasibility of Emergency Flood Traffic Road Damage Assessment by Integrating Remote Sensing Images and Social Media Information
Enhanced earthquake impact analysis based on social media texts via large language model
A text mining analytic approach for distinguishing between disaster and non-disaster zones from tweets
Disaster information mining from a social perception perspective
Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical events
Toward satisfactory public accessibility
Analyzing public response to wildfires
Introduction to Information Retrieval
Enriching Word Vectors with Subword Information
Rapid assessment of disaster damage using social media activity
Support-Vector Networks
The random subspace method for constructing decision forests
Long Short-Term Memory
Integrating strong-motion recordings and twitter data for a rapid shakemap of macroseismic intensity
An uncertainty-aware framework for reliable disaster damage assessment via crowdsourcing
Exploratory analysis of barriers to effective post-disaster recovery
Data collection tools for post-disaster damage assessment of building and lifeline infrastructure systems
Information fusion for automated post-disaster building damage evaluation using deep neural network
Twitter and Facebook are not representative of the general population
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
Understanding the Political Representativeness of Twitter Users
The Digital Divide Among Twitter Users and Its Implications for Social Research
Disaster damage assessment from the tweets using the combination of statistical features and informative words
| Unique citing works | 9 |
|---|---|
| Citations per year | 4,5 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |